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Kousik, N. V.
- Autonomous Greedy Routing in Wireless Sensor Networks
Abstract Views :195 |
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Authors
Affiliations
1 Department of Computing Science and Engineering, Galgotias University, IN
2 Department of Information Technology, Lebanese French University, IQ
1 Department of Computing Science and Engineering, Galgotias University, IN
2 Department of Information Technology, Lebanese French University, IQ
Source
ICTACT Journal on Communication Technology, Vol 10, No 1 (2019), Pagination: 1947-1952Abstract
Routing is challenging issue in WSN: Cryptography and key management schemes seem good, but they are too expensive in WSN. Prevention-based and detection based are the two approaches that are used in MANET. In prevention-based approaches a centralized key management is required, These applications require a good Quality of Service (QoS) from sensor networks, such as, minimum percentage of sensor coverage in the required area, continuous service during required time slot with minimum (or limited) resources (like sensor energy and channel bandwidth) and minimum outside intervention. The whole network may be affected if the infrastructure is destroyed. So this approach is used to prevent misbehavior, but not detect malicious based routes Detection based approaches are used to detect selfish node along with route that helps to identify malicious misbehavior route. Detection based approaches are based on trust in MANETs. Hence this approach is used to calculate the trust value in trust management schemes. The proposed scheme differentiates, routes, data packets and control packets, and also excludes the other causes that results in dropping packets, such as unreliable wireless connections and buffer overflows. The proposed scheme in a MANET routing protocol, evaluation of the AODV (Adhoc on demand on distance vector) and Low Energy Adaptive Clustering Hierarchy (LEACH) protocol with the NS2 simulator.Keywords
MANET, WSN, Routing, Quality of Service, AODV.
References
- M.A. Rahman, M.S. Islam and A. Talevski, “Performance Measurement of Various Routing Protocols in Ad-Hoc Network”, Proceedings of International Multi Conference of Engineers and Computer Scientists, pp. 18-20, 2009.
- R.P. Gupta, D.V.K. Sharma and V.M. Shrimal, “Investigation of Different Parameters of Dynamic Source Routing with varied Terrain Areas and Pause Time for Wireless Sensor Network”, International Journal of Modern Engineering Research, Vol. 1, No. 2, pp. 626-631, 2011.
- J.N. Al-Karaki and A.E. Kamal, “Routing Techniques in Wireless Sensor Networks: A Survey”, IEEE Wireless Communications, Vol. 11, No. 6, pp. 6-28, 2004.
- T. Van Dam and K. Langendoen, “An Adaptive Energy-Efficient MAC Protocol for Wireless Sensor Networks”, Proceedings of 1st International Conference on Embedded Networked Sensor Systems, pp. 171-180, 2003.
- Vijay Mohan Shrimal, Ravindra Prakash Gupta and Virendra Kumar Sharma, “Investigation of Adhoc Topology AODV for Wireless Sensor Networks for Varying Terrain Areas for Different Speed (Node Speed)”, International Journal of Advanced Research in Computer Science and Software Engineering, Vol. 2, No. 1, pp. 12-18, 2012.
- L. Breslau, D. Estrin, K. Fall, S. Floyd, J. Heidemann, A. Helmy and H. Yu, “Advances in network simulation”, Computer, Vol. 33, No. 5, pp. 59-67, 2000.
- K. Fall and K. Varadhan, “The ns Manual (formerly ns Notes and Documentation)”, Available at: https://www.isi.edu/nsnam/ns/doc/ns_doc.pdf.
- Imad Aad, Mohammad Hossein Manshaei and Jean Pierre Hubaux, “ns2 for the Impatient”, Available at: http://www.manshaei.org/files/HoE-ns2-Mobnet09.pdf.
- A. Aziz, S. Rahayu, N.A. Endut, S. Abdullah, M. Daud and M. Norazman, “Performance Evaluation of AODV, DSR and DYMO Routing Protocol in MANET”, Scientific Research Journal, Vol. 5, No. 2, pp. 49-65, 2008.
- I.F. Akyildiz, W. Su, Y. Sankarasubramaniam and E. Cayirci, “Wireless Sensor Networks: A Survey”, Computer Networks, Vol. 38, No. 4, pp. 393-422, 2002.
- Privacy Preservation of Micro Data Publishing using Fragmentation
Abstract Views :178 |
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Authors
Affiliations
1 Department of Computer Science and Engineering, Anna University, Chennai, IN
2 Department of Computer Science and Engineering, SRM Institute of Science and Technology, IN
3 Department of Computing Science and Engineering, Galgotias University, IN
1 Department of Computer Science and Engineering, Anna University, Chennai, IN
2 Department of Computer Science and Engineering, SRM Institute of Science and Technology, IN
3 Department of Computing Science and Engineering, Galgotias University, IN
Source
ICTACT Journal on Soft Computing, Vol 9, No 3 (2019), Pagination: 1945-1949Abstract
Organization such as hospitals, publish detailed data or micro data about individuals for research or statistical purposes. Many applications that employ data mining techniques involve mining data that include private and sensitive information about the subjects. When releasing the micro data, it is necessary to prevent the sensitive information of the individuals from being disclosed. Several existing privacy-preserving approaches focus on anonymization techniques such as generalization and bucketization. Recent work has shown that generalization loses considerable amount of information for high dimensional data, the bucketization does not prevent membership disclosure and does not make clear separation between quasi-identifying attributes and sensitive attributes. In this work a novel technique called Fragmentation is proposed for publishing sensitive data with preventing the sensitive information of the individual. Here first the vertical Fragmentation is applied to attributes. In vertical Fragmentation, attributes are segmented into columns. Each column contains a subset of attributes. Secondly, the horizontal Fragmentation is applied to tuples. In this, tuples are segmented into buckets. Each bucket contains a subset of tuples. Finally the real dataset is used for experiments and the results show that this Fragmentation technique preserves better utility while protecting privacy threats and prevents the membership disclosure.Keywords
Privacy, Privacy Preservation, Data Anonymization, Data Publishing, Data Security.References
- Tiancheng Li, Nninghui Li, Jian Zhang and Ian Molloy, “Slicing: A New Approach for Privacy Preserving Data Publishing”, IEEE Transactions on Knowledge and Data Engineering, Vol. 24, No. 3, pp. 561-574, 2012.
- C. Aggarwal, “On K-Anonymity and the Curse of Dimensionality”, Proceedings of 31st International Conference on Very Large Data Bases, pp. 901-909, 2005.
- J. Brickell and V. Shmatikov, “The Cost of Privacy: Destruction of Data-Mining Utility in Anonymized Data Publishing”, Proceedings of 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 70-78, 2008.
- D.R. Kumar Raja and S. Pushpa, “Diversifying Personalized Mobile Multimedia Application Recommendations through the Latent Dirichlet Allocation and Clustering Optimization”, Multimedia Tools and Applications, pp. 1-20, 2019.
- N. Koudas, D. Srivastava, T. Yu, and Q. Zhang, “Aggregate Query Answering on Anonymized Tables”, Proceedings of International Conference on Data Engineering, pp. 116-125, 2007.
- K. LeFevre, D. DeWitt and R. Ramakrishnan, “Mondrian Multidimensional K-Anonymity”, Proceedings of International Conference on Data Engineering, pp. 20-25, 2006.
- K. Raja and S. Pushpa, “Novelty‐Driven Recommendation by using Integrated Matrix Factorization and Temporal‐Aware Clustering Optimization”, International Journal of Communication Systems, pp. 1-16, 2018.
- N. Li, T. Li and S. Venkatasubramanian, “T-Closeness: Privacy Beyond k-Anonymity and ‘-Diversity”, Proceedings of International Conference on Data Engineering, pp. 106-115, 2007.
- T. Li and N. Li, “On the Tradeoff between Privacy and Utility in Data Publishing”, Proceedings of International Conference on Knowledge Discovery and Data Mining, pp. 517-526, 2009.
- D.J. Martin, D. Kifer, A. Machanavajjhala, J. Gehrke and J.Y. Halpern, “Worst-Case Background Knowledge for Privacy- Preserving Data Publishing”, Proceedings of International Conference on Knowledge Discovery and Data Mining, pp. 126-135, 2007.
- U. Selvi and S. Puspha, “A Review of Big Data an Anonymization Algorithms”, International Journal of Applied Engineering Research, Vol. 10, No, 17, pp. 13125-13130, 2015.
- L. Sweeney, “Achieving K-Anonymity Privacy Protection using Generalization and Suppression”, International Journal of Uncertainty Fuzziness and Knowledge-Based Systems, Vol. 10, No. 6, pp. 571-588, 2002.
- M. Terrovitis, N. Mamoulis, and P. Kalnis, “Privacy-Preserving Anonymization of Set-Valued Data”, Proceedings of 31st International Conference on Very Large Data Bases, pp. 115-125, 2008.
- R.C.W. Wong, J. Li, A.W.C. Fu and K. Wang, “(α, k)-Anonymity: An Enhanced k-Anonymity Model for Privacy Preserving Data Publishing”, Proceedings of International Conference on Knowledge Discovery and Data Mining, pp. 754-759, 2006.
- X. Xiao and Y. Tao, “Anatomy: Simple and Effective Privacy Preservation”, Proceedings of 31st International Conference on Very Large Data Bases, pp. 139-150, 2006.
- J. Xu, W. Wang, J. Pei, X. Wang, B. Shi, and A.W.C. Fu, “Utility- Based Anonymization Using Local Recoding”, Proceedings of International Conference on Knowledge Discovery and Data Mining, pp. 785-790, 2006.
- Benjamin C.M. Fung, Ke Wang, Ada Wai-Chee Fu, and Philip S. Yu, “Introduction to Privacy-Preserving Data Publishing: Concepts and Techniques”, CRC Press, 2011.
- Clustering Algorithm Networks Test Cost Sensitive for Specialist Divisions
Abstract Views :189 |
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Authors
Affiliations
1 School of Computing Science and Engineering, Galgotias University, IN
2 Department of Computer Science and Engineering, Malla Reddy Institute of Technology and Science, IN
1 School of Computing Science and Engineering, Galgotias University, IN
2 Department of Computer Science and Engineering, Malla Reddy Institute of Technology and Science, IN
Source
ICTACT Journal on Image and Video Processing, Vol 10, No 2 (2019), Pagination: 2098-2102Abstract
It has been proven that deeper Convolutional Neural Networks (CNN) can result in better accuracy in many problems, but this accuracy comes with a high computational cost. Also, input instances have not the same difficulty. As a solution for accuracy vs. computational cost dilemma, we introduce a new test-cost-sensitive method for convolution neural networks. This method trains a CNN with a set Based on the difficulty of the input instance, the expert branches decide to use a shallower part of the network or go deeper to the end. The expert branches learn to determine: is the current network prediction wrong and if the instance passed to deeper network layers it will generate the right output; if not, then the expert branches will stop the process of computation. The experimental results on the standard CIFAR-10 dataset indicate that in comparison with basic models, the proposed method can train models with lower test cost and competitive accuracy.Keywords
Test-Cost-Sensitive Learning, Deep Learning, CNN with Expert Branches, Instance-Based Cost.References
- S.P.S. Gurjar, S. Gupta and R. Srivastava, “Automatic Image Annotation Model using LSTM Approach”, Signal and Image Processing: An International Journal, Vol. 8, No. 4, pp. 25-37, 2017.
- S. Maity, M. Abdel-Mottaleb and S.S. Asfour, “Multimodal Biometrics Recognition from Facial Video via Deep Learning”, Signal and Image Processing: An International Journal, Vol. 8, No. 1, pp. 67-75, 2017.
- K. He, X. Zhang, S. Ren and J. Sun, “Deep Residual Learning for Image Recognition”, Proceedings of International Conference on Computer Vision, pp. 1-9, 2015.
- D. Kadam, A.R. Madane, K. Kutty and B.S.V. Bonde, “Rain Streaks Elimination Using Image Processing Algorithms”, Signal and Image Processing: An International Journal, Vol. 10, No. 3, pp. 21-32, 2019.
- A. Massaro, V. Vitti and A. Galiano, “Automatic Image Processing Engine Oriented on Quality Control of Electronic Boards”, Signal and Image Processing: An International Journal, Vol. 9, No. 2, pp. 1-14, 2018.
- X. Li, Z. Liu, P. Luo, C. Change Loy and X. Tang, “Not All Pixels Are Equal: Difficulty-Aware Semantic Segmentation via Deep Layer Cascade”, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 3193-3202, 2017.
- M. Naghibi, R. Anvari, A. Forghani and B. Minaei, “Cost-Sensitive Topical Data Acquisition from the Web”, International Journal of Data Mining and Knowledge Management Process, Vol. 9, No. 3, pp. 39-56, 2019.
- A. Polyak and L. Wolf, “Channel-Level Acceleration of Deep Face Representations”, IEEE Access, Vol. 3, pp. 2163-2175, 2015.
- A. Lavin and S. Gray, “Fast Algorithms for Convolutional Neural Networks”, Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition, pp. 4013-4021, 2016.
- L. J. Ba and R. Caruana, “Do Deep Nets Really Need to be Deep?”, Proceedings of International Conference on Advances in Neural Information Processing Systems, pp. 2654-2662, 2014.
- A. Romero, N. Ballas, S.E. Kahou, A. Chassang, C. Gatta and Y. Bengio, “Fitnets: Hints for Thin Deep Nets”, Proceedings of International Conference on Neural and Evolutionary Computing, pp. 782-789, 2014.
- X. Zhang, J. Zou, K. He and J. Sun, “Accelerating Very Deep Convolutional Networks for Classification and Detection”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 38, No. 1, pp. 1943-1955, 2015.
- E.L. Denton, W. Zaremba, J. Bruna, Y. LeCun and R. Fergus, “Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation”, Proceedings of 27th International Conference on Neural Information Processing Systems, pp. 1269-1277, 2014.
- M. Jaderberg, A. Vedaldi and A. Zisserman, “Speeding Up Convolutional Neural Networks with Low Rank Expansions”, Proceedings of International Conference on Computer Vision and Pattern Recognition, pp. 1-12, 2014.
- N. Strom, “Sparse Connection and Pruning in Large Dynamic Artificial Neural Networks”, Proceedings of 5th European Conference on Speech Communication and Technology, pp. 1-4, 1997.
- G.E. Hinton, N. Srivastava, A. Krizhevsky, I. Sutskever and R.R. Salakhutdinov, “Improving Neural Networks by Preventing Co-Adaptation of Feature Detectors”, Proceedings of International Conference on Computer Vision and Pattern Recognition, pp. 1-18, 2012.
- N. Vasilache, J. Johnson, M. Mathieu, S. Chintala, S. Piantino and Y. LeCun, “Fast Convolutional Nets with FBFFT: A GPU Performance Evaluation”, Proceedings of International Conference on Learning Representations, pp. 1-17, 2014.
- M. Mathieu, M. Henaff and Y. LeCun, “Fast Training of Convolutional Networks through FFTs”, Proceedings of International Conference on Neural and Evolutionary Computing, pp. 1111-1119, 2013.
- V.N. Murthy, V. Singh, T. Chen, R. Manmatha and D. Comaniciu, “Deep Decision Network for Multi-Class Image Classification”, Proceedings of IEEE conference on Computer Vision and Pattern Recognition, pp. 2240-2248, 2016.
- V. Vanhoucke, A. Senior and M.Z. Mao, “Improving the Speed of Neural Networks on CPUs”, Proceedings of International Workshop on Deep Learning and Unsupervised Feature Learning, pp. 1-8, 2011.
- A. Toshev and C. Szegedy, “Deeppose: Human Pose Estimation via Deep Neural Networks”, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 1653-1660, 2014.
- A. Krizhevsky and G. Hinton, “Learning Multiple Layers of Features from Tiny Images”, Technical Report, University of Toronto, pp. 1-65, 2009.
- C. Szegedy, V. Vanhoucke, S. Ioffe, J. Shlens and Z. Wojna, “Rethinking the Inception Architecture for Computer Vision”, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 2818-2826, 2016.
- Flight Plan Route Optimization And Increase The Profit In Airline Industry By Using Hybrid BCF Algorithm
Abstract Views :200 |
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Authors
Affiliations
1 School of Computing Science and Engineering, Galgotias University, IN
1 School of Computing Science and Engineering, Galgotias University, IN
Source
ICTACT Journal on Communication Technology, Vol 10, No 3 (2019), Pagination: 2019-2023Abstract
Airline industry is a booming industry where decisions have to be taken in the dynamic environment. There are many factors which govern the decision-making namely the airline route as considerate amount of profit can be generated by selecting the optimized airline route. The paper proposes a hybrid BCF algorithm which optimizes the flight trajectory and seat allotments. The algorithm specifically optimizes the airline route, seat allotment on a large scale of data set to give the best option to choose in and implement it. The result shows the tremendous variation regarding the net amount there by increasing the profit.Keywords
Hybrid BCF Algorithm, Decision-Making, Optimized, Airline Route, Profit.References
- X.S. Yang, “Firefly Algorithm, Stochastic Test Functions and Design Optimisation”, International Journal of BioInspired Computation, Vol. 2, No. 2, pp. 78-84, 2010.
- X.S. Yang, “Nature-Inspired Metaheuristic Algorithms”, Luniver Press, 2008.
- X.S. Yang, “Firefly Algorithms for Multimodal Optimization”, Proceedings of International Symposium on Stochastic Algorithms, pp. 169-178, 2009.
- X.S. Yang, “Biology Derived Algorithms in Engineering Optimization”, Chapter 32, Handbook of Bioinspired Algorithms and Applications, Chapmann & Hall/CRC Press, pp. 589-600, 2005.
- International Airline Activity-Time Series, Available at: https://bitre.gov.au/publications/ongoing/international_airli ne_activity-time_series.aspx
- D. Shilane, J. Martikainen, S. Dudoit and S.J. Ovaska, “A General Framework for Statistical Performance Comparison of Evolutionary Computation Algorithms”, Information Sciences, Vol. 178, No. 14, pp. 2870-2879, 2008.
- Jian Chai, Zhong Yu Zhang, Shou-Yang Wang, Kin Keung Lai and John Liu, “Aviation Fuel Demand Development in China”, Energy Economics, Vol. 46, pp. 224-235, 2014.
- Olivier Dessens, Marcus O. Kohler, Helen L. Rogers, Rod L. Jones and John A. Pyle, “Aviation and climate change”, Transport Policy, Vol. 34, No. 2, pp. 14-20, 2014.
- Hideki Fukui and Koki Nagata, “Flight Cancellation as a Reaction to the Tarmac Delay Rule: An Unintended Consequence of Enhanced Passenger Protection”, Economics of Transportation, Vol. 3, No. 1, pp. 29-44, 2014.
- Shangyao Yan and Ching-Hui Tang, “A Heuristic Approach for Airport Gate Assignments for Stochastic Flight Delays”, European Journal of Operational Research, Vol. 180, No. 2, pp. 547-567, 2007.
- Christian Kiss-Toth and Gabor Takacs, “A Dynamic Programming Approach for 4D Flight Route Optimization”, Proceedings of IEEE International Conference on Big Data, pp. 24-28, 2014.
- IBM, “Websphere MQ”, Available at: https://www.ibm.com/support/knowledgecenter/en/SSFKSJ _8.0.0/com.ibm.mq.explorer.doc/e_queues.htm
- D. Fisher, R. DeLine, M. Czerwinski and S. Drucker, “Interactions with Big Data Analytics”, Interactions, Vol. 13, No. 3, pp. 50-59, 2012.
- Elton Fernandesa and R.R. Pacheco, “Transport Efficient use of Airport Capacity”, Transportation Research Part A Policy and Practice, Vol. 36, No. 3, pp. 225-238, 2002.
- X.S. Yang, “A New Metaheuristic Bat-Inspired Algorithm in Nature Inspired Cooperative Strategies for Optimization”, Proceedings of International Conference on Studies in Computational Intelligence, 65-74, 2010.
- X.S. Yang and S. Deb, “Cuckoo Search via Levy flight”, Proceedings of World Congress on Nature and Biologically Inspired Computing, pp. 210-214, 2009.
- X.S. Yang, “Bat Algorithm: Literature Review and Applications”, International Journal of Bio-Inspired Computation, Vol. 5, No. 3, pp. 141-149, 2013.
- X.S. Yang, “Firefly Algorithm, Levy Flights and Global Optimization”, Proceedings of International Conference on Research and Development in Intelligent Systems, pp. 209218, 2010.
- Gulsah Hancerliogullari, Ghaith Rabadi, Ameer H. AlSalem and Mohamed Kharbeche, “Greedy Algorithms and Metaheuristics for a Multiple Runway Combined Arrival Departure Aircraft Sequencing Problem”, Journal of Air Transport Management, Vol. 32, pp. 39-48, 2013.
- J.A.D. Atkin, E.K. Burke, J.S. Greenwood and D. Reeson, “A Metaheuristic Approach to Aircraft Departure Scheduling at London Heathrow Airport”, Computer Aided Systems of Public Transport, Vol. 600, pp. 235-252, 2008.
- Momin Jamil, “A Literature Survey of Benchmark Functions for Global Optimisation Problems”, International Journal on Mathematical Modelling and Numerical Optimisation, Vol. 4, No. 2, pp. 1-12, 2013.
- Lisa Davison, Clare Littleford and Tim Ryley, “Air Travel Attitudes and Behaviours: The Development of Environment-Based Segments”, Journal of Air Transport Management, Vol. 36, pp. 13-22, 2014.
- L. Zhe, W.A. Chaovalitwongse, H.C. Huang and E.L. Johnson, “Network Model for Aircraft Routing Problem”, Transportation Science, Vol. 45, No. 1, pp. 109-120, 2011.
- Y. Suzuki, J.E. Tyworth and R.A. Novack, “Airline Market Share and Customer Service Quality: a ReferenceDependent Model”, Transportation Research Part A: Policy and Practice, Vol. 35, No. 9, pp. 773-788, 2001.
- S. Ruther, “A Multi-Commodity Flow Formulation for the Integrated Aircraft Routing, Crew Pairing, and Tail Assignment Problem”, Proceedings of 45th Annual Conference of Operations Research Society of New Zealand, pp. 1-6, 2010.
- E. Kasturi, S. Prasanna Devi, S. Vinu Kiran and S. Manivannan, “Airline Route Profitability Analysis and Optimization using Big Data Analytics on Aviation Data Sets under Heuristic Techniques”, Procedia Computer Science, Vol. 87, pp. 86-92, 2016.
- System Framework and Data Communication for Named Data Networking: NDN
Abstract Views :145 |
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Authors
Affiliations
1 Department of Information Technology, Mookambigai College of Engineering, IN
2 School of Computing Science and Engineering, Galgotias University, Greater Noida, IN
3 Department of Computer Science, Ministry of Education, AE
1 Department of Information Technology, Mookambigai College of Engineering, IN
2 School of Computing Science and Engineering, Galgotias University, Greater Noida, IN
3 Department of Computer Science, Ministry of Education, AE
Source
ICTACT Journal on Communication Technology, Vol 11, No 3 (2020), Pagination: 2239-2242Abstract
Socialist modernization has been steadily applied with the ongoing advancement of research and technology. Communication network’s broad coverage area has made the electronic communication network technologies well established and deployed in our region. Computer networking has now become a part of the everyday life of the people. Communications infrastructure technology has added comfort and pleasure to the work and life of people within the context with the ever-increasing size of communication networks. Concerning that current online network is predominantly IP, any kind of online application of Named Data Networking (NDN) requires conservative system engineering to support NDN somehow, and also handle IP traffic simultaneously. This paper is taking Ethernet, the one of the very common local area network (LAN) technology. Our experience indicates that due to the absence of existing cross-platform APIs, the introduction of a new communication protocol stack for D2D communication on different platforms may be a challenging technological problem.Keywords
Network Security, Route Safeguards, Content Delivery Network, DNS-Based Server Redirecting, Named Data Networking, Local Area Network, Computer Communication.- CMOS Based Driver Tree Design for Microprocessor Clock Distribution Units Iin Biomedical Image Processing Circuits
Abstract Views :130 |
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Authors
V. Sujatha
1,
S. Ravindrakumar
2,
D. Sasikala
3,
V. M. Senthil Kumar
4,
N. V. Kousik
5,
Jayasri Subramaniam
6
Affiliations
1 Department of Electronics and Communication Engineering, Shree Sathyam College of Engineering and Technology, IN
2 Department of Biomedical Engineering, Sri Shakthi Institute of Engineering and Technology, IN
3 Department of Electronics and Communication Engineering, Muthayammal Engineering College, IN
4 Department of Electronics and Communication Engineering, Malla Reddy College of Engineering and Technology, IN
5 Department of School of Computing Science and Engineering, Galgotias University, IN
6 Division of Computing, University of Northampton, GB
1 Department of Electronics and Communication Engineering, Shree Sathyam College of Engineering and Technology, IN
2 Department of Biomedical Engineering, Sri Shakthi Institute of Engineering and Technology, IN
3 Department of Electronics and Communication Engineering, Muthayammal Engineering College, IN
4 Department of Electronics and Communication Engineering, Malla Reddy College of Engineering and Technology, IN
5 Department of School of Computing Science and Engineering, Galgotias University, IN
6 Division of Computing, University of Northampton, GB
Source
ICTACT Journal on Microelectronics, Vol 7, No 1 (2021), Pagination: 1080-1084Abstract
The transmission of clock signal is done across the integrated circuit in the presence of buffers and wires in synchronous biomedical systems on-chip architectures. This paper presents the investigation of the driver tree architecture to be used in microprocessor and DSP processors for biomedical image processing applications for clock distribution. In system on chip architecture this design plays an important role. Several clock distribution units like parallel, H-Bridge configurations were implemented in past. A new buffer is designed for the improvement of driving capability in clock distribution. This paper presents the CMOS based clock distribution circuit with better power and drive current. The parameters like power and current are investigated. Predictive technology models for CMOS 90nm technology are used.Keywords
CMOS, Current Driver, Clock Driver, H-Bridge, Buffer, Power.References
- H. Zhu and V. Kursun, “2-Phase High-Frequency Clock Distribution with SPLIT-IO Dual-Vt Repeaters for Suppressed Leakage Currents”, Proceedings of IEEE International Symposium on Circuits and Systems, pp. 2932-2935, 2015.
- K. Gundu and V. Kursun, “Low Leakage Clock Tree with Dual-Threshold-Voltage Split Input-Output Repeaters”, IEEE Transactions on Very Large Scale Integration (VLSI) Systems, Vol. 27, No. 7, pp. 1537-1547, 2019.
- K. Athikulwongse, X. Zhao and S.K. Lim, “Buffered Clock Tree Sizing for Skew Minimization under Power and Thermal Budgets”, Proceedings of IEEE International Conference on Design Automation, pp. 474-479, 2010.
- K. Niitsu, M. Sakurai, N. Harigai, T.J. Yamaguchi and H. Kobayashi, “CMOS Circuits to Measure Timing Jitter using a Self-Referenced Clock and a Cascaded Time Difference Amplifier with Duty-Cycle Compensation”, IEEE Journal on Solid-State Circuits, Vol. 47, No. 11, pp. 2701-2710, 2012.
- L. Ravezzi and H. Partovi, “Clock and Synchronization Networks for a 3 GHz 64 Bit ARMv8 8-Core SoC”, IEEE Journal on Solid-State Circuits, Vol. 50, No. 7, pp. 1702-1710, 2015.
- M. Dave, M. Jain, M.S. Baghini and D. Sharma, “A Variation Tolerant Current-Mode Signaling Scheme for On-Chip Interconnects”, IEEE Transactions on Very Large Scale Integration (VLSI) Systems, Vol. 21, No. 2, pp. 342-353, 2013.
- P. Hao and S. Chen, “Single-Event Transient Susceptibility Analysis and Evaluation Methodology for Clock Distribution Network in the Integrated Circuit Working in Real Time”, IEEE Transactions on Device and Materials Reliability, Vol. 17, No. 3, pp. 539-548, 2017.
- R. Islam and M.R. Guthaus, “CMCS: Current-Mode Clock Synthesis”, IEEE Transactions on Very Large Scale Integration (VLSI) Systems, Vol. 25, No. 3, pp. 1054-1062, 2017.
- R. Islam, H. Fahmy, P.Y. Lin and M.R. Guthaus, “Differential Current-Mode Clock Distribution”, Proceedings of Midwest Symposium on Circuits and Systems, pp. 1-4, 2015.
- S.J. Park, N. Natu and M. Swaminathan, “Analysis Design and Prototyping of Temperature Resilient Clock Distribution Networks for 3-D ICs”, IEEE Transactions on Components, Packaging and Manufacturing Technology, Vol. 5, No. 11, pp. 1669-1678, 2015.
- Todri Sanial and Y. Cheng, “A Study of 3-D Power Delivery Networks with Multiple Clock Domains”, IEEE Transactions on Very Large Scale Integration (VLSI) Systems, Vol. 24, No. 11, pp. 3218-3231, 2016.
- V.F. Pavlidis, I. Savidis and E.G. Friedman, “Clock Distribution Networks in 3-D Integrated Systems”, IEEE Transactions on Very Large Scale Integration (VLSI) Systems, Vol. 19, No. 12, pp. 2256-2266, 2011.
- X. Chen, T. Zhu, W. Davis and P.D. Franzon, “Adaptive and Reliable Clock Distribution Design for 3-D Integrated Circuits”, IEEE Transactions on Components, Packaging and Manufacturing Technology, Vol. 4, No. 11, pp. 1862-1870, 2014.
- X. Zhao, J. Minz and S.K. Lim, “Low-Power and Reliable Clock Network Design for Through-Silicon Via (TSV) based 3D ICs”, IEEE Transactions on Components, Packaging and Manufacturing Technology, Vol. 1, No. 2, pp. 247-259, 2011.
- X.W. Shih and Y.W. Chang, “Fast Timing-Model Independent Buffered Clock-Tree Synthesis”, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, Vol. 31, No. 9, pp. 1393-1404, 2012.
- Ravindrakumar, Joselyn, “Design of Low Power Blink Detector for Minimally Invasive Implantable Stimulator (SOC) using 180nm Technology”, Advances in Intelligent and Soft Computing, 2014.
- Ravindrakumar, Joselyn, “Design of New Implantable Stimulator Chip (SoC) for Non-Invasive/Minimally Invasive Biomedical Application”, Proceedings of International Conference on Communications and Signal Processing, pp. 1-5, 2014.
- V.M. Senthilkumar, A. Muruganandham, S. Ravindrakumar and N.S. Gowri Ganesh, “FINFET Operational Amplifier with Low Offset Noise and High Immunity to Electromagnetic Interference”, Microprocessors and Microsystems, Vol. 71, pp.1-22, 2019.
- V.M. Senthilkumar, S. Ravindrakumar and D. Nithya,“A Vedic Mathematics Based Processor Core for Discrete Wavelet Transform using FinFET and CNTFET Technology for Biomedical Signal Processing”, Microprocessors and Microsystems, Vol. 71, pp.2221-2228, 2019.
- S. Ravindrakumar, “High Speed, Low Matchline Voltage Swing and Search Line Activity TCAM Cell Array Design in 14nm FinFET Technology”, Proceedings of International Conference on Emerging Trends in Electrical, Communication and Information Technologies, pp. 1-12, 2018.
- V.M. Senthilkumar and S. Ravindrakumar, “A Low Power and Area Efficient FinFET Based Approximate Multiplier In 32nm Technology”, Proceedings of International Conference on Soft Computing and Signal Processing, pp. 1-12, 2018.
- M. Senthilkumar and S. Ravindrakumar, “Design of Adiabatic Array Logic Adder using Multigate Device in 32nm FinFET Process Technology”, Journal of Advanced Research in Dynamical and Control Systems, Vol. 22, No. 2, pp. 464-472, 2018.